Applied AI Engineer

About the role

Fuse Energy is an energy startup building a fully integrated energy company, from its own solar and battery projects to grid infrastructure, real-time power trading and distributed energy in homes. It is building a cutting-edge AI team and is hiring an Applied AI Engineer. The role suits someone interested in applied AI that improves the energy experience for customers and internal operations. You will work on consumer features using VLM and LLM tools, and build AI tools and agents that make teams across Fuse more productive, from customer support to warehouses and back office. This is an applied engineering role, not pure research: you will own what you build, from specification to production.

Key responsibilities

• Ship AI features for customers, such as personalised energy recommendations and onboarding from an energy bill
• Build LLM applications and agents for support, engineering, warehouse and back-office teams, including multi-agent systems and durable workflows (e.g. Temporal)
• Build the engineering around them: cloud infrastructure, integrations and access control so users and agents only reach what they should
• Own evaluation: datasets, golden answers, human and LLM judges, A/B tests, and know whether a change genuinely helped
• Choose models by performance, latency and cost, and revisit them as models improve
• Work with trading, operations and backend teams so models reflect real-time market conditions, energy pricing and demand and weather forecasts
• Monitor AI systems in production and keep them reliable

Required profile

• 3+ years of experience, with requirements varying by role level
• Experience owning an applied AI system end to end, ideally in a startup or small team, and able to explain what broke and how you knew it worked
• A software engineer who moved into applied AI, or an ML engineer who writes production code
• Analytical, rigorous and quick to learn; you do not need the exact tools, just the ability to pick them up

Required skills

• Solid Python (or similar) and experience deploying LLMs or VLMs into production
• Solid understanding of cloud technologies, containerisation and scalable AI applications
• Bonus: PyTorch or TensorFlow; forecasting, weather and demand modelling; energy markets and trading; fine-tuning or RL; vision, document or NLP pipelines; agent runtimes and MCP

What we offer

• Competitive salary and eligibility for equity
• Biannual bonus scheme
• Fully expensed tech to match your needs
• Private health insurance
• Breakfast and dinner allowance for office-based employees
• Benefits may vary by location as the company hires globally